> For the complete documentation index, see [llms.txt](https://know.rendernetwork.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://know.rendernetwork.com/using-ai-generation-tools/using-ai-workflows-on-the-render-network-from-image-to-3d-and-back-again.md).

# Using AI Workflows on the Render Network – From Image to 3D & Back Again

{% embed url="<https://youtu.be/pjludsHbAbw>" %}

In this tutorial, we dive deep into how Render Network helps enable powerful AI workflows that loop back into your creative process.

It’s not about one-off generations - it’s about building scalable, flexible pipelines that let you move from concept to 3D with ease.

**What you’ll learn:**\
• Using **Photon** for image-to-image object ideation\
• Editing, rotating, and compositing objects with **Flux Kontext**\
• Converting AI images to 3D with **Hunyuan3D 2.5**\
• Exporting to DCCs and rigging with **Mixamo**\
• How these tools work together within the **Render Network**

Whether you’re prototyping, building secondary scene assets, or exploring new ideas – this is a creative flex that will change how you think about AI and 3D.\
The real strength of AI isn’t the tool - it’s the workflow you design.

Try using Render today at: [render.x.io](https://render.x.io/)

**The Render Network features:**&#x20;

• **Photon** - AI image-to-image\
• **Flux Kontext** - Editing and multi-view compositing\
• **Hunyuan3D 2.5** - 20 free generations daily - 3d.hunyuan.tencent.com\
• **Mixamo** - Free character animation


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://know.rendernetwork.com/using-ai-generation-tools/using-ai-workflows-on-the-render-network-from-image-to-3d-and-back-again.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.